Data sharing is a critical component of any research project, and it’s something we’ve made easier with the interactive Share and Publish features within Ingenuity Variant Analysis. Many research teams have taken advantage of this functionality to share data with colleagues or the entire community in the case of papers they’ve submitted for publication. A recent example comes from a team led by Peter Krawitz of the Charité University Medicine in Berlin.

In the American Journal of Human Genetics (AJHG, a Cell Press journal), Krawitz and colleagues recently published an exome study of individuals thought to be harboring mutations affecting proteins involved in the synthesis of glycosylphosphatidylinositol (GPI) anchors. In recent years, mutations in eight genes involved in the GPI-anchor-synthesis pathway have been shown to cause a wide phenotypic spectrum of disorders with intellectual disability and seizures; these range from syndromic forms with characteristic physical malformations and minor anomalies to nonsyndromic forms. Congenital disorders that are caused by an impairment of GPI-anchor synthesis and maturation are now classified as congenital disorders of glycosylation, a diverse class of metabolic diseases.

In the paper, Krawitz and colleagues identified four different mutations in three unrelated families by using independent strategies. In family A, recruited based on the physical features of postnatal microcephaly, a combination of traditional microarray-based autozygosity mapping and exome sequencing identified a missense variant in PGAP3, a gene linked to GPI-anchor maturation, as the only likely candidate. In families B and C, mutations were uncovered in the same gene via a targeted sequencing approach in a cohort of individuals ascertained specifically for intellectual disability and hyperphosphatasia.

In this study, scientists screened rare variants using the interactive filter cascade in Variant Analysis, which helped them to eliminate common and non-deleterious variants. Ultimately, they homed in on variations in the homozygous region of chromosome 17 and predicted that they were deleterious. The data supporting their findings have been made available for review by the authors and can be found online. People wishing to view the analysis can access it with a free Variant Analysis account.

The process of publishing these data required a simple click of the Publish button by the research team. This first step allowed the authors to embargo the custom URL until their manuscript was accepted and published. They were then able to update it with the final title and journal and click “release” once the paper was published. Releasing a data set allows Ingenuity to make the data publicly and perpetually accessible via the custom URL the researchers created. The analysis parameters used in the published study will persist with the data set, meaning each time it is accessed, users will see how others have analyzed it.

To learn more about the Share and Publish features of Variant Analysis, please visit the product page or contact us.